In episode one we optimized Torch A3C performance on the new Intel Xeon Phi (Knight's Landing) CPU. Arm MAP and Performance Reports identified bottlenecks in our framework and sped up model training by 7x.

To get further gains we found areas of the…

I’ve always enjoyed playing games, but the buzz from writing programs that play games has repeatedly claimed months of my conscious thought at a time. I’m not sure that writing programs that write programs that play games is the perfect solution, but…

In February, a new paper from Google's DeepMind team appeared on arxiv. This one was interesting – they showed dramatically improved performance and training time of their Atari-playing Deep Q-Learning network. The training speedup was so great that…

In the previous post we parallelized Andrej Karpathy's policy gradient code to see whether a very simple implementation coupled with supercomputer speeds could learn to play Atari Pong faster than the state-of-the-art (DeepMind's A3C at time of…